摘要
疏勒河下游的瓜州绿洲水资源形成困难、水环境脆弱,属国家极端干旱荒漠自然保护区。研究利用加入动量项的BP神经网络并基于时间序列对1993年至2008年双塔水库水质指标年均值进行模拟和预测,确定模型参数为:输入节点数2,输出节点数1,隐含层数2,最小训练速率0.1,动态参数0.6,SIGMOID函数调整值0.9,允许误差0.0001,最大迭代次数10000。模型拟合相对误差值小于5%,预测检验误差小于10%。根据预测结果,水库在2009年至2013年属II类水质,水质符合生活以及农业灌溉用水标准,但仍存在富营养化的风险。
Guazhou oasis locates in downstream of Shulehe River Basin,belongs to national extreme arid desert nature reserve,and the formation of its water resources is difficult,and the ecological environment is fragile.BP neural network model which based on the time series and addition of the momentum term was used to model and predict the annual average of water quality indicators in Shuangta Reservoir from 1993 to 2008.And the parameters of the model are the followings,the number of the enter nodes is 2,the number of the output nodes is 1,the number of the hidden layers is 2,minimum training rate is 0.1,dynamic parameters is 0.6,adjusted value of the SIGMOID function is 0.9,permissible error is 0.0001,maximum number of iterations is 10000.Moreover,the value of the relative error of model fitting is less than 5%,and the value of the relative error in the stage of prediction testing is less than 10%.According to the results of the water prediction,the water quality from 2009 to 2013 is belong to Class II grade which meets the standards of domestic and agricultural irrigation water use,however,the water has the risk of eutrophication.
出处
《水资源与水工程学报》
2012年第6期149-153,共5页
Journal of Water Resources and Water Engineering
关键词
水资源
水质预测
BP神经网络
双塔水库
疏勒河下游
water resources
water quality prediction
BP neural network
Shuangta reservoir
lower reaches of Shulehe River
